A Generalized State of the Art Model for Precise Visualization and Analysis of Defected Portions of Fruits Using Choice Based Segmentation Technique

There are number of computer vision based quality analysis of products and process have been developed in the past where image analysis and image understanding plays a key role in the systems for faithful operation. In this paper, we have developed a generalized state of the art model for fruit inspection and defect detection based on external features of fruit images. As fruits are exported and imported in volume and it becomes difficult for farmers to check each and every fruit manually. Hence, the proposed novel approach will provide an efficient interactive tool between the user and the system. This generalized model gives a close analysis of fruit images under different image segmentation methods for better image understanding in computer vision. The proposed technique helps in analyzing the defected fruit portions accurately.